{"id":"https://openalex.org/W4315778606","doi":"https://doi.org/10.1109/access.2023.3236575","title":"Feature Interpretation Using Generative Adversarial Networks (FIGAN): A Framework for Visualizing a CNN\u2019s Learned Features","display_name":"Feature Interpretation Using Generative Adversarial Networks (FIGAN): A Framework for Visualizing a CNN\u2019s Learned Features","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4315778606","doi":"https://doi.org/10.1109/access.2023.3236575"},"language":"en","primary_location":{"id":"doi:10.1109/access.2023.3236575","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3236575","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/10005208/10015730.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/10005208/10015730.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5025843483","display_name":"Kyle Hasenstab","orcid":"https://orcid.org/0000-0002-4687-960X"},"institutions":[{"id":"https://openalex.org/I26538001","display_name":"San Diego State University","ror":"https://ror.org/0264fdx42","country_code":"US","type":"education","lineage":["https://openalex.org/I26538001"]},{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kyle A. Hasenstab","raw_affiliation_strings":["Department of Mathematics and Statistics, San Diego State University, San Diego, CA, USA","Department of Radiology, University of California at San Diego, San Diego, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-4687-960X","affiliations":[{"raw_affiliation_string":"Department of Mathematics and Statistics, San Diego State University, San Diego, CA, USA","institution_ids":["https://openalex.org/I26538001"]},{"raw_affiliation_string":"Department of Radiology, University of California at San Diego, San Diego, CA, USA","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065749378","display_name":"Justin Huynh","orcid":"https://orcid.org/0000-0002-4640-6124"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Justin Huynh","raw_affiliation_strings":["Department of Radiology, University of California at San Diego, San Diego, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-4640-6124","affiliations":[{"raw_affiliation_string":"Department of Radiology, University of California at San Diego, San Diego, CA, USA","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107962689","display_name":"Samira Masoudi","orcid":"https://orcid.org/0000-0002-5266-2386"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Samira Masoudi","raw_affiliation_strings":["Halıcıoğlu Data Science Institute, University of California at San Diego, San Diego, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Halıcıoğlu Data Science Institute, University of California at San Diego, San Diego, CA, USA","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035078986","display_name":"Guilherme Moura Cunha","orcid":"https://orcid.org/0000-0001-6403-5155"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Guilherme M. Cunha","raw_affiliation_strings":["Department of Radiology, University of Washington, Seattle, WA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiology, University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018321151","display_name":"Michael J. Pazzani","orcid":"https://orcid.org/0000-0002-4240-7349"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael Pazzani","raw_affiliation_strings":["Halıcıoğlu Data Science Institute, University of California at San Diego, San Diego, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-4240-7349","affiliations":[{"raw_affiliation_string":"Halıcıoğlu Data Science Institute, University of California at San Diego, San Diego, CA, USA","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084967705","display_name":"Albert Hsiao","orcid":"https://orcid.org/0000-0002-9412-1369"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Albert Hsiao","raw_affiliation_strings":["Department of Radiology, University of California at San Diego, San Diego, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-9412-1369","affiliations":[{"raw_affiliation_string":"Department of Radiology, University of California at San Diego, San Diego, CA, USA","institution_ids":["https://openalex.org/I36258959"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":3.9428,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":{"value":0.92875274,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"11","issue":null,"first_page":"5144","last_page":"5160"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12859","display_name":"Cell Image Analysis Techniques","score":0.982200026512146,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T12859","display_name":"Cell Image Analysis Techniques","score":0.982200026512146,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9807000160217285,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9749000072479248,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7957489490509033},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7283735275268555},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7104621529579163},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6491084694862366},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6415932178497314},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.47988784313201904},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4152401387691498},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38083699345588684}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7957489490509033},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7283735275268555},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7104621529579163},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6491084694862366},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6415932178497314},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.47988784313201904},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4152401387691498},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38083699345588684},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2023.3236575","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3236575","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/10005208/10015730.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:9ee2e806bfbd4c7e94a74b38f9293e5e","is_oa":true,"landing_page_url":"https://doaj.org/article/9ee2e806bfbd4c7e94a74b38f9293e5e","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 11, Pp 5144-5160 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2023.3236575","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3236575","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/10005208/10015730.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5831839224","display_name":"RAPID: Explainable Machine Learning for Analysis of COVID-19 Chest CT","funder_award_id":"2026809","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320332603","display_name":"University of California, San Diego","ror":"https://ror.org/0168r3w48"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4315778606.pdf","grobid_xml":"https://content.openalex.org/works/W4315778606.grobid-xml"},"referenced_works_count":47,"referenced_works":["https://openalex.org/W1849277567","https://openalex.org/W1901129140","https://openalex.org/W1988511720","https://openalex.org/W2073503722","https://openalex.org/W2123045220","https://openalex.org/W2516809705","https://openalex.org/W2809254203","https://openalex.org/W2892868976","https://openalex.org/W2900003150","https://openalex.org/W2958089299","https://openalex.org/W2962770929","https://openalex.org/W2962851944","https://openalex.org/W2962858109","https://openalex.org/W2963073614","https://openalex.org/W2969880113","https://openalex.org/W2971527746","https://openalex.org/W2979200397","https://openalex.org/W2985068832","https://openalex.org/W2997591727","https://openalex.org/W2999356287","https://openalex.org/W3005352289","https://openalex.org/W3008003211","https://openalex.org/W3029137193","https://openalex.org/W3035574324","https://openalex.org/W3036319923","https://openalex.org/W3047625747","https://openalex.org/W3161150081","https://openalex.org/W3200379731","https://openalex.org/W3202023533","https://openalex.org/W3213449503","https://openalex.org/W3214627974","https://openalex.org/W3216717225","https://openalex.org/W4283803492","https://openalex.org/W4293861706","https://openalex.org/W4304083970","https://openalex.org/W6677995690","https://openalex.org/W6685133223","https://openalex.org/W6717255582","https://openalex.org/W6718140377","https://openalex.org/W6718379498","https://openalex.org/W6734194636","https://openalex.org/W6736518430","https://openalex.org/W6737947904","https://openalex.org/W6739575509","https://openalex.org/W6750391026","https://openalex.org/W6765779288","https://openalex.org/W6779243538"],"related_works":["https://openalex.org/W2068608913","https://openalex.org/W4293226380","https://openalex.org/W3124914020","https://openalex.org/W2141033859","https://openalex.org/W2077542787","https://openalex.org/W2156434174","https://openalex.org/W2071701083","https://openalex.org/W2383687187","https://openalex.org/W2070401501","https://openalex.org/W2121496884"],"abstract_inverted_index":{"Convolutional":[0],"neural":[1],"networks":[2],"(CNNs)":[3],"are":[4,26,77],"increasingly":[5],"being":[6],"explored":[7],"and":[8,151,187,196],"used":[9,30,115],"for":[10,22,51,60,99,119],"a":[11,45,96,117,125,138,173],"variety":[12],"of":[13,34,47,113,137,175,181],"classification":[14,120],"tasks":[15],"in":[16],"medical":[17],"imaging,":[18],"but":[19],"current":[20],"methods":[21,31,76],"post":[23],"hoc":[24],"explainability":[25,167],"limited.":[27],"Most":[28],"commonly":[29],"highlight":[32],"portions":[33],"the":[35,73,86,135,154,179],"input":[36],"image":[37,188],"that":[38,133,153],"contribute":[39],"to":[40,79,130,146,177,193],"classification.":[41],"While":[42],"this":[43],"provides":[44,111],"form":[46],"spatial":[48],"localization":[49,89],"relevant":[50],"focal":[52],"disease":[53,64],"processes,":[54],"it":[55],"may":[56],"not":[57],"be":[58],"sufficient":[59],"co-localized":[61],"or":[62,70,121],"diffuse":[63,81],"processes":[65],"such":[66],"as":[67],"pulmonary":[68],"edema":[69],"fibrosis.":[71],"For":[72],"latter,":[74],"new":[75],"required":[78],"isolate":[80],"texture":[82],"features":[83,114],"employed":[84],"by":[85,116,165],"CNN":[87,118],"where":[88],"alone":[90],"is":[91],"ambiguous.":[92],"We":[93,143],"therefore":[94],"propose":[95],"novel":[97],"strategy":[98],"eliciting":[100],"explainability,":[101],"called":[102],"Feature":[103],"Interpretation":[104],"using":[105],"Generative":[106],"Adversarial":[107],"Networks":[108],"(FIGAN),":[109],"which":[110],"visualization":[112],"regression.":[122],"FIGAN":[123,145],"uses":[124],"conditional":[126],"generative":[127],"adversarial":[128],"network":[129],"synthesize":[131],"images":[132],"span":[134],"range":[136],"CNN\u2019s":[139],"principal":[140],"embedded":[141],"features.":[142],"apply":[144],"two":[147],"previously":[148],"developed":[149],"CNNs":[150],"show":[152],"resulting":[155],"feature":[156],"interpretations":[157],"can":[158],"clarify":[159],"ambiguities":[160],"within":[161],"attention":[162],"areas":[163],"highlighted":[164],"existing":[166],"methods.":[168],"In":[169],"addition,":[170],"we":[171],"perform":[172],"series":[174],"experiments":[176],"study":[178],"effect":[180],"auxiliary":[182],"segmentations,":[183],"training":[184],"sample":[185],"size,":[186],"resolution":[189],"on":[190],"FIGAN\u2019s":[191],"ability":[192],"provide":[194],"consistent":[195],"interpretable":[197],"synthetic":[198],"images.":[199]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":2}],"updated_date":"2026-06-22T08:00:12.763002","created_date":"2025-10-10T00:00:00"}